Hyperspectral reflectance data, molecular and weights for trained model

Supplementary data for the paper: <i>"Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel."</i><b>"maize_2020_unl_reflectance_traits.csv</b> " contains hyperspectral reflectance data and molecular traits for a maize diversity panel grown in Lincoln, Nebraska in 2020.<b>"weights.h5"</b> are the weights of the autoencoder model used to reduce dimensionality of the hyperspectral reflectance data in this study.<b>"</b><b>maize_2020_unl_reflectance_traits.csv" </b>contains the latent variables/reduced dimensions of the hyperspectral reflectance data used in this study.<br>